We built an AI that spots problems in your product data

I built a tool called Counsel that connects to your product and revenue stack (PostHog, Stripe, GA4, GitHub, Linear, Gmail, Slack, Notion, etc.) and runs a continuous analysis loop to surface insights, anomalies, missed opportunities, and suggested actions.

The goal is simple: founders often have the data but not the time to dig through it. Counsel tries to close that gap by running a weekly insight cycle. It generates hypotheses, tests them across your data sources, and produces a ranked list of findings. Examples: checkout friction, retention patterns, activation dropoffs, failed onboarding paths, pricing bottlenecks, unhandled error clusters, correlation between support volume and feature releases.

Right now we are running a private pilot with a few early stage B2C SaaS teams. They keep telling us the value comes from the insights they were not expecting. Small things they did not know to look for.

We are still early but would love feedback from HN.

If you want to try it, we are opening a small set of new pilot spots. Happy to share the technical details, architecture decisions, or lessons from building multi source agents if that is useful.

Link: https://www.withcounsel.co

Happy to answer any questions.

Please don't capture my cursor on your homepage, and if you have to, please don't apply smoothing to is so that it doesn't go where I want it to! I appreciate that it's pretty, but making your site annoying to use can only increase churn